Published on: 2024-02-05 03:15:59
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Unsupervised Machine Learning Hidden Markov Models in Python is a course from Udemy that explains Markov’s hidden model for stock price analysis, language modeling, website statistics, and biology. Markov’s hidden model is generally related to sequels. Many of the data that are suitable for building the model are included in the sequence. For example, stock value is a sequence of prices and language is a sequence of words. In short, sequels are everywhere, and having the ability to analyze them is an essential skill in data science.
In this tutorial, you will learn how to measure the probability distribution of a sequence of random variables and learn a lot about deep learning. During this time we work with Theano and Tensorflow libraries and fully explain the hidden model of Markov. This course examines many of Markov’s models and Markov’s hidden model, as well as how to analyze and predict disease and health models.
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Subtitle: English
Quality: 720p
Changes:
Version 2020/12 compared to 2018/10 has increased the number of 1 lesson and the duration of 12 minutes.
Version 2023/11 compared to 2020/12 has increased the number of 2 lessons and the duration of 33 minutes.
1.99 GB
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